Improving photovoltaic efficiency: a systematic study of P&O and INC MPPT techniques

Abstract

Achieving high efficiency in photovoltaic (PV) systems under fluctuating irradiance and temperature conditions relies on effective maximum power point tracking (MPPT) techniques. Among the most commonly adopted approaches, perturb and observe (P&O) and incremental conductance (INC) are favored for their ease of implementation and operational flexibility. Nevertheless, a systematic comparison of their performance under dynamic conditions remains limited. This study conducts a comparative evaluation of P&O and INC algorithms using MATLAB/Simulink, with emphasis on tracking accuracy, convergence speed, and overall efficiency. A standard PV module is exposed to rapid variations in irradiance and temperature to examine algorithm robustness. The results indicate that although P&O achieves fast convergence in steady-state operation, it exhibits noticeable oscillations around the maximum power point, resulting in efficiency losses of up to 3%. Conversely, the INC method offers improved tracking precision and reduced oscillations, yielding efficiency gains of 2-4% over P&O in dynamic environments. These findings underline the trade-off between algorithmic simplicity and tracking accuracy, and provide practical guidance for selecting MPPT strategies in both grid-connected and standalone PV applications.